The Crucial Role of Programming Languages in Today’s World
The research paper explores the evolution and crucial role of programming languages in shaping the digital era, emphasizing their significance in diverse fields such as technology, education, innovation, and global connectivity. Additionally, it delves into the current trends in programming languages, with a focus on Python and JavaScript, and highlights the importance of mobile application testing in ensuring a seamless user experience. The conclusion underscores the integral role of programming languages in our technologically-driven society.
Published by: Kaustubh Khangate, Anuj Kishor Rahatwal, Paras Vishal Kanade
Author: Kaustubh Khangate
Paper ID: V10I1-1141
Paper Status: published
Published: January 11, 2024
Advancements in Artificial Intelligence: Impacts on Society and Ethics
This research paper delves into the intricate interplay between Artificial Intelligence (AI) and computer engineering, exploring its historical roots, current state, societal impacts, ethical considerations, regulatory frameworks, and future prospects. From tracing the evolution of AI in computer engineering to anticipating future technological advancements, the narrative unfolds within the broader context of societal transformation. The examination of ethical dimensions and regulatory challenges underscores the need for responsible development and governance. As AI becomes increasingly integrated into computer engineering, this research aims to provide a comprehensive understanding of its multifaceted impacts and guide a thoughtful approach to navigating the evolving landscape. This research paper delves into the intricate interplay between Artificial Intelligence (AI) and computer engineering, exploring its historical roots, current state, societal impacts, ethical considerations, regulatory frameworks, and future prospects. From tracing the evolution of AI in computer engineering to anticipating future technological advancements, the narrative unfolds within the broader context of societal transformation. The examination of ethical dimensions and regulatory challenges underscores the need for responsible development and governance. As AI becomes increasingly integrated into computer engineering, this research aims to provide a comprehensive understanding of its multifaceted impacts and guide a thoughtful approach to navigating the evolving landscape. This research paper delves into the intricate interplay between Artificial Intelligence (AI) and computer engineering, exploring its historical roots, current state, societal impacts, ethical considerations, regulatory frameworks, and future prospects. From tracing the evolution of AI in computer engineering to anticipating future technological advancements, the narrative unfolds within the broader context of societal transformation. The examination of ethical dimensions and regulatory challenges underscores the need for responsible development and governance. As AI becomes increasingly integrated into computer engineering, this research aims to provide a comprehensive understanding of its multifaceted impacts and guide a thoughtful approach to navigating the evolving landscape.
Published by: Dhanashree Kolhe, Jeel Mange, Gautamii Sinkar
Author: Dhanashree Kolhe
Paper ID: V10I1-1139
Paper Status: published
Published: January 11, 2024
Blockchain Technology
Blockchain is a method of recording information that makes it impossible or difficult for the system to be changed, hacked, or manipulated
Published by: Prapti Chaware, Adhyatmika Ghodvinde, Harshal Gawade
Author: Prapti Chaware
Paper ID: V9I6-1243
Paper Status: published
Published: January 6, 2024
Phishing mail detection using bidirectional LSTM
Phishing attacks have become a major concern in today's digital world, where malicious actors try to dupe unsuspecting individuals into divulging sensitive information. The need for effective methods to detect phishing emails has become crucial. In this study, we propose a novel approach for phishing mail detection using Bidirectional Long Short-Term Memory (BiLSTM) networks. BiLSTM networks are a type of recurrent neural network (RNN) that can capture temporal dependencies in sequential data. Our approach leverages the power of BiLSTM networks to analyze the content and structure of emails for identifying phishing attempts. We preprocess the email data by converting them into sequential tokenized representations. These representations are then fed into the BiLSTM network to learn the patterns and features associated with phishing emails. We train our model using a large dataset of labeled phishing and non-phishing emails. Experimental results demonstrate that our proposed approach achieves high detection accuracy, outperforming traditional machine learning algorithms. The ability of BiLSTM networks to capture both past and future contextual information allows our model to effectively identify phishing emails based on their content and structural properties. With the increasing sophistication of phishing attacks, the development of robust and accurate detection systems is paramount. Our approach contributes to this goal by providing an efficient and reliable method for detecting phishing emails, thereby enhancing the security of individuals and businesses
Published by: Vusa Vamsi Krishna
Author: Vusa Vamsi Krishna
Paper ID: V9I6-1235
Paper Status: published
Published: January 3, 2024
A comparison of Machine Learning techniques for predicting IMDb score of movies
In the world of film industry analytics, predicting the success of movies based on various input features has garnered considerable attention in recent times. This research is important because it can help people in the movie industry make better decisions. It allows them to allocate resources effectively, minimize risks, and enhance the overall success of movie projects. This research paper presents and compares different machine learning techniques to predict the IMDb score of movies by leveraging multiple input features such as release date, genre, budget, gross revenue, profit, number of votes, country of origin, director, actor, writer, production studio, and runtime. We also account for the inflation rate over the years while considering the monetary attributes. We explore two methods: one where we transform and reduce the data using techniques like one-hot encoding and PCA, and another where we use label encoding for categorical data. In the first method, we try three models: Support Vector Regressor (SVR), RandomForest Regressor, and Recurrent Neural Network (RNN). In the second method, we use RandomForest Regressor, Gradient Boosting Regressor, and LightGBM Regressor. We measure how well these models predict by looking at Mean Squared Error (MSE) and R-squared. This research helps provide people in the film industry with insights into what factors contribute to a movie's success.
Published by: Anubhav Mathur, Snigdha Patil
Author: Anubhav Mathur
Paper ID: V9I6-1241
Paper Status: published
Published: January 3, 2024
Impact of cultural factors and gender roles on maternal parenting in India
Purpose: To analyse the role of cultural factors and gender roles on maternal parenting in India Study design: Self report questionnaire Methodology: Sixty women in the age range of 35-73 reported their response through a self-report questionnaire Results: Majority of the women who participated in the survey strongly or moderately agreed that Indian culture does play a significant role in mothers labour participation. Majority also agreed that they are unemployed in-order to take care of family- an important gender role in India. Conclusion: results of the current study reveal that Indian culture and gender roles have played a significant role in the level of maternal employment
Published by: Aarohi Shah
Author: Aarohi Shah
Paper ID: V9I6-1238
Paper Status: published
Published: January 1, 2024
